The Classification of Sini Decoction Pattern in Traditional Chinese Medicine by Gene Expression Profiling

Hung-Tsu Cheng; Chaang-Ray Chen; Chia-Yang Li; Chao-Ying Huang; Wun-Yi Shu; Ian C Hsu

doi:10.1155/2016/8239817

The Classification of Sini Decoction Pattern in Traditional Chinese Medicine by Gene Expression Profiling

Evid Based Complement Alternat Med. 2016:2016:8239817. doi: 10.1155/2016/8239817. Epub 2016 Apr 20.

Authors

Hung-Tsu Cheng¹, Chaang-Ray Chen², Chia-Yang Li³, Chao-Ying Huang², Wun-Yi Shu⁴, Ian C Hsu²

Affiliations

¹ Institute of Nano Engineering and Microsystems, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, Hsinchu 300, Taiwan; Classics Chinese Medicine Clinic, Taipei 104, Taiwan.
² Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 300, Taiwan.
³ Department of Genome Medicine, College of Medicine and Center for Infectious Disease and Cancer Research, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
⁴ Institute of Statistics, National Tsing Hua University, Hsinchu 300, Taiwan.

Abstract

We investigated the syndromes of the Sini decoction pattern (SDP), a common ZHENG in traditional Chinese medicine (TCM). The syndromes of SDP were correlated with various severe Yang deficiency related symptoms. To obtain a common profile for SDP, we distributed questionnaires to 300 senior clinical TCM practitioners. According to the survey, we concluded 2 sets of symptoms for SDP: (1) pulse feels deep or faint and (2) reversal cold of the extremities. Twenty-four individuals from Taipei City Hospital, Linsen Chinese Medicine Branch, Taiwan, were recruited. We extracted the total mRNA of peripheral blood mononuclear cells from the 24 individuals for microarray experiments. Twelve individuals (including 6 SDP patients and 6 non-SDP individuals) were used as the training set to identify biomarkers for distinguishing the SDP and non-SDP groups. The remaining 12 individuals were used as the test set. The test results indicated that the gene expression profiles of the identified biomarkers could effectively distinguish the 2 groups by adopting a hierarchical clustering algorithm. Our results suggest the feasibility of using the identified biomarkers in facilitating the diagnosis of TCM ZHENGs. Furthermore, the gene expression profiles of biomarker genes could provide a molecular explanation corresponding to the ZHENG of TCM.